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DBMS > Apache Druid vs. Dolt vs. Splice Machine vs. SwayDB

System Properties Comparison Apache Druid vs. Dolt vs. Splice Machine vs. SwayDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDolt  Xexclude from comparisonSplice Machine  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA MySQL compatible DBMS with Git-like versioning of data and schemaOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.96
Rank#193  Overall
#90  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orggithub.com/­dolthub/­dolt
www.dolthub.com
splicemachine.comswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.dolthub.comsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsDoltHub IncSplice MachineSimer Plaha
Initial release2012201820142018
Current release29.0.1, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJavaScala
Server operating systemsLinux
OS X
Unix
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyesyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
HTTP REST
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infocurrently in alpha releaseyes infoJavano
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemOnly one user is configurable, and must be specified in the config file at startupAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache DruidDoltSplice MachineSwayDB
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